Serum Glycomics Profiling of Patients with Primary Restless Legs Syndrome Using LC–MS/MS

Analyzing N-Glycans in Cerebrospinal Fluid: A Glycomics Approach

Cerebrospinal fluid (CSF) plays a crucial role in direct interaction with the brain, making it an essential sample for identifying molecular markers that emerge as neurological disorders progress. Notably, changes in protein glycosylation are observed in many neurodegenerative diseases. However, analyzing the glycome profile of CSF is challenging due to low protein concentration. N-glycans are chemically modified through permethylation to quantify these changes accurately and analyzed using a highly sensitive liquid chromatography-mass spectrometry (LC-MS) technique. This study outlines a method for preparing samples with optimized conditions for N-glycan digestion combined with a sensitive detection system. The approach has proven reliable and consistent in measuring various permethylated N-glycans extracted from CSF.

Identification of Causal Genes and Potential Drug Targets for Restless Legs Syndrome: A Comprehensive Mendelian Randomization Study

Background: Restless legs syndrome (RLS) is a common sensorimotor sleep disorder that affects sleep quality of life. Much effort has been made to make progress in RLS pharmacotherapy; however, patients with RLS still report poor long-term symptom control. Methods: Comprehensive Mendelian randomization (MR) was performed to search for potential causal genes and drug targets using the cis-pQTL and RLS GWAS data. Robustness was validated using the summary-based Mendelian randomization (SMR) method and co-localization analysis. Further evidence of pleiotropy of the target genes and their potential side effects was provided by phenome-wide MR analysis (MR-PheWAS). Finally, molecular docking simulations were conducted on drug candidates corresponding to these targets, which revealed promising binding affinities and interaction patterns and underscored the druggable potential of the target gene. All of the analyses above were conducted in the context of Homo sapiens. Results:MAN1A2 showed a statistically significant result in the MR analysis, which was validated through SMR and co-localization analysis. The MR-PheWAS showed a low probability of pleiotropy and prospective side effects. Molecular docking was used to visualize the binding structure and fine affinity for MAN1A2 and the drugs predicted by DSigDB. Conclusions: Our study provides comprehensive evidence supporting MAN1A2 as a promising causal gene and therapeutic target for RLS, offering insights into the underlying molecular mechanisms and paving the way for future drug development efforts.

Current Analytical Methods and Challenges for the Clinical Diagnosis of Invasive Pulmonary Aspergillosis Infection

In the last decade, pulmonary fungal infections such as invasive pulmonary aspergillosis (IPA) have increased in incidence due to the increased number of immunocompromised individuals. This increase is especially problematic when considering mortality rates associated with IPA are upwards of 70%. This high mortality rate is due to, in part, the length of time it takes to diagnose a patient with IPA. When diagnosed early, mortality rates of IPA decrease by as much as 30%. In this review, we discuss current technologies employed in both medical and research laboratories to diagnose IPA, including culture, imaging, polymerase chain reaction, peptide nucleic acid-fluorescence in situ hybridization, enzyme-linked immunosorbent assay, lateral flow assay, and liquid chromatography mass spectrometry. For each technique, we discuss both promising results and potential areas for improvement that would lead to decreased diagnosis time for patients suspected of contracting IPA. Further study into methods that offer increased speed and both analytical and clinical sensitivity to decrease diagnosis time for IPA is warranted.

Serum N-Glycan Profiling of Patients with Narcolepsy Type 1 Using LC-MS/MS

The neurological condition known as narcolepsy type 1 (NT1) is an uncommon condition marked by extreme daytime sleepiness, cataplexy, sleep paralysis, hallucinations, disrupted nocturnal sleep, and low or undetectable levels of orexin in the CSF fluid. NT1 has been hypothesized to be an immunological disorder; its treatment is currently only symptomatic, and misdiagnosis is not uncommon. This study compares the N-glycome of NT1 patients with healthy controls in search of potential glycan biomarkers using LC-MS/MS. A total of 121 candidate N-glycans were identified, 55 of which were isomeric N-glycan structures and 65 were not. Seventeen N-glycan biomarker candidates showed significant differences between the NT1 and control cohorts. All of the candidate glycan biomarkers were isomeric except HexNAc6Hex7Fuc0NeuAc1 (6701) and HexNAc6Hex7Fuc1NeuAc2 (6712). Therefore, with isomeric and nonisomeric structures, a total of 20 candidate N-glycan biomarkers are reported in this study, and interestingly, all are either sialylated or sialylated-fucosylated and upregulated in NT1 relative to the control. The distribution levels of all the identified N-glycans show that the sialylated glycan type is the most abundant in NT1 and is majorly disialylated, although the trisialylated subtype is three-fold higher in NT1 compared to the healthy control. The first isomers of HexNAc5Hex6Fuc0NeuAc3 (5603), HexNAc6Hex7Fuc0NeuAc2 (6702), and HexNAc6Hex7Fuc1NeuAc4 (6714) expressed a high level of fold changes (FC) of 1.62, 2.19, and 2.98, respectively. These results suggest a different N-glycome profile of NT1 and a relationship between sialylated glycan isomers in NT1 disease development or progression. The revelation of N-glycan expression alterations in this study may improve NT1 diagnostic methods, understanding of NT1 pathology, and the development of new targeted therapeutics.

Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

Unveiling the pathophysiology of restless legs syndrome through transcriptome analysis

The aim of this study was to analyze signaling pathways associated with differentially expressed messenger RNAs in people with restless legs syndrome (RLS). Seventeen RLS patients and 18 controls were enrolled. Coding RNA expression profiling of 12,857 gene transcripts by next-generation sequencing was performed. Enrichment analysis by pathfindR tool was carried-out, with p-adjusted ≤0.001 and fold-change ≥2.5. Nine main different network groups were significantly dysregulated in RLS: infections, inflammation, immunology, neurodegeneration, cancer, neurotransmission and biological, blood and metabolic mechanisms. Genetic predisposition plays a key role in RLS and evidence indicates its inflammatory nature; the high involvement of mainly neurotropic viruses and the TORCH complex might trigger inflammatory/immune reactions in genetically predisposed subjects and activate a series of biological pathways-especially IL-17, receptor potential channels, nuclear factor kappa-light-chain-enhancer of activated B cells, NOD-like receptor, mitogen-activated protein kinase, p53, mitophagy, and ferroptosis-involved in neurotransmitter mechanisms, synaptic plasticity, axon guidance, neurodegeneration, carcinogenesis, and metabolism.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Toolbox Accelerating Glycomics (TAG): Improving Large-Scale Serum Glycomics and Refinement to Identify SALSA-Modified and Rare Glycans

Glycans are involved in many fundamental cellular processes such as growth, differentiation, and morphogenesis. However, their broad structural diversity makes analysis difficult. Glycomics via mass spectrometry has focused on the composition of glycans, but informatics analysis has not kept pace with the development of instrumentation and measurement techniques. We developed Toolbox Accelerating Glycomics (TAG), in which glycans can be added manually to the glycan list that can be freely designed with labels and sialic acid modifications, and fast processing is possible. In the present work, we improved TAG for large-scale analysis such as cohort analysis of serum samples. The sialic acid linkage-specific alkylamidation (SALSA) method converts differences in linkages such as α2,3- and α2,6-linkages of sialic acids into differences in mass. Glycans modified by SALSA and several structures discovered in recent years were added to the glycan list. A routine to generate calibration curves has been implemented to explore quantitation. These improvements are based on redefinitions of residues and glycans in the TAG List to incorporate information on glycans that could not be attributed because it was not assumed in the previous version of TAG. These functions were verified through analysis of purchased sera and 74 spectra with linearity at the level of R2 > 0.8 with 81 estimated glycan structures obtained including some candidate of rare glycans such as those with the N,N’-diacetyllactosediamine structure, suggesting they can be applied to large-scale analyses.

Exploring serum glycome patterns after moderate to severe traumatic brain injury: A prospective pilot study

BACKGROUND

Glycans play essential functional roles in the nervous system and their pathobiological relevance has become increasingly recognized in numerous brain disorders, but not fully explored in traumatic brain injury (TBI). We investigated longitudinal glycome patterns in patients with moderate to severe TBI (Glasgow Coma Scale [GCS] score ≤12) to characterize glyco-biomarker signatures and their relation to clinical features and long-term outcome.

METHODS

This prospective single-center observational study included 51 adult patients with TBI (GCS ≤12) admitted to the neurosurgical unit of the University Hospital of Pecs, Pecs, Hungary, between June 2018 and April 2019. We used a high-throughput liquid chromatography-tandem mass spectrometry platform to assess serum levels of N-glycans up to 3 days after injury. Outcome was assessed using the Glasgow Outcome Scale-Extended (GOS-E) at 12 months post-injury. Multivariate statistical techniques, including principal component analysis and orthogonal partial least squares discriminant analysis, were used to analyze glycomics data and define highly influential structures driving class distinction. Receiver operating characteristic analyses were used to determine prognostic accuracy.

FINDINGS

We identified 94 N-glycans encompassing all typical structural types, including oligomannose, hybrid, and complex-type entities. Levels of high mannose, hybrid and sialylated structures were temporally altered (p<0·05). Four influential glycans were identified. Two brain-specific structures, HexNAc5Hex3DeoxyHex0NeuAc0 and HexNAc5Hex4DeoxyHex0NeuAc1, were substantially increased early after injury in patients with unfavorable outcome (GOS-E≤4) (area under the curve [AUC]=0·75 [95%CI 0·59-0·90] and AUC=0·71 [0·52-0·89], respectively). Serum levels of HexNAc7Hex7DeoxyHex1NeuAc2 and HexNAc8Hex6DeoxyHex0NeuAc0 were persistently increased in patients with favorable outcome, but undetectable in those with unfavorable outcome. Levels of HexNAc5Hex4DeoxyHex0NeuAc1 were acutely elevated in patients with mass lesions and in those requiring decompressive craniectomy.

INTERPRETATION

In spite of the exploratory nature of the study and the relatively small number of patients, our results provide to the best of our knowledge initial evidence supporting the utility of glycomics approaches for biomarker discovery and patient phenotyping in TBI. Further larger multicenter studies will be required to validate our findings and to determine their pathobiological value and potential applications in practice.

FUNDING

This work was funded by the Italian Ministry of Health (grant number GR-2013-02354960), and also partially supported by a NIH grant (1R01GM112490-08).

Isomeric separation of permethylated glycans by extra-long reversed-phase liquid chromatography (RPLC)-MS/MS

Glycosylation is known as a critical biological process that can largely affect the properties and the functions of proteins. Glycan isomers have been shown to be involved in a variety of disease progressions. However, the separation and identification of glycan isomers has been a challenge for years due to the microheterogeneity of glycan isomeric structures. Therefore, effective and stable techniques have been investigated over the last few decades to improve isomeric separations of glycans. RPLC has been widely used in biomolecule analysis because of its extraordinary reproducibility and reliability in retention time and separation resolution. However, so far, no studies have achieved high resolution of glycan isomers using this technique. In this study, we focused on further boosting the isomeric separation of permethylated glycans using a 500 mm reversed-phase LC column. To achieve better resolutions on permethylated glycans, different LC conditions were optimized using glycan standards, including core- and branch-fucosylated N-glycan isomers and sialic acid linked isomers, which were both successfully separated. Then, the optimal separation strategy was applied to achieve separations of N- and O-glycan isomers derived from model glycoproteins, including bovine fetuin, ribonuclease B and κ-casein. Baseline separations were observed on multiple sialylated linkage isomers. However, the separation performance of high-mannose isomers needs further improvement. The reproducibility and stability of this long C18 column was also tested by doing run-to-run, day-to-day and month-to-month comparisons of retention times on multiple glycans and the %RSD was found less than 0.92%. Finally, we applied this approach to separate glycan isomers derived from complex biological samples, including blood serum and cell lines, where baseline separations were attained on several isomeric structures. Compared to the separation efficiency of PGC and MGC columns, the RPLC C18 column provides lower resolution but more robust reproducibility, which makes it a good complementary alternative for isomeric separations of glycans.

Advances in mass spectrometry-based glycomics-An update covering the period 2017-2021

The wide variety of chemical properties and biological functions found in proteins is attained via post-translational modifications like glycosylation. Covalently bonded to proteins, glycans play a critical role in cell activity. Complex structures with microheterogeneity, the glycan structures that are associated with proteins are difficult to analyze comprehensively. Recent advances in sample preparation methods, separation techniques, and MS have facilitated the quantitation and structural elucidation of glycans. This review focuses on highlighting advances in MS-based techniques for glycomic analysis that occurred over the last 5 years (2017-2021) as an update to the previous review on the subject. The topics of discussion will include progress in glycomic workflow such as glycan release, purification, derivatization, and separation as well as the topics of ionization, tandem MS, and separation techniques that can be coupled with MS. Additionally, bioinformatics tools used for the analysis of glycans will be described.

The relationship between sleep disorders, anxiety, depression, and cognitive function with restless legs syndrome (RLS) in the elderly

OBJECTIVES

Restless legs syndrome (RLS) has a significant effect on sleep and quality of life. Delays in diagnosis and treatment are frequent due to a lack of awareness. In this study, a clinical analysis was performed to examine the relationship between sleep, mood, and cognitive function in RLS.

METHODS

According to the Pittsburgh Sleep Quality Index score (PSQI), patients with RLS were divided into a sleep disorders group (SD, PSQI > 7) and non-sleep disorders group (NSD, PSQI ≤ 7). Healthy controls were selected as a control group matched for age, cultural background, and marital status. We compared differences between the three groups using the Hamilton Anxiety Scale (HAMA), Hamilton Depression (HAMD), Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). The SD and NSD groups were also assessed with the Restless Leg Syndrome Rating Scale (RLSRS) and the severity of RLS between the two groups was compared. The analysis used t-test, ANOVA, and Pearson correlation.

RESULTS

(1) Among the 54 RLS patients, 30 people in the control group, 35 patients with sleep disorders (SD, 65%), and 19 patients without sleep disorders (NSD, 35%), there were no significant differences in age, educational level, marital status, or trauma history. (2) The comparison results of the case group (SD and NSD) and the control group showed highly significant differences (P < 0.01) in the PSQI-HAMA-HAMD score but no significant differences between the NSD group, the SD group, and the control group in MMSE score. There was no difference between the NSD group and the control group in the MoCA, but a significant difference (P < 0.05) between the SD group and the control group was found. (3) The comparison between the NSD and the SD groups revealed significant differences in the RLSRS, HAMA, and HAMD scores (P < 0.05), but there were no statistical differences (P > 0.05) between two groups on MMSE and MoCA score. (4) Correlation and regression showed that there was a linear correlation between PSQI scores and RLSRS and HAMD scores in patients with RLS (P < 0.05). The regression equation was PSQI =  - 2.393 + 0.494 RLSRS + 0.170 HAMD.

CONCLUSIONS

RLS patients were prone to sleep disorders, anxiety, and depression. Sleep disorders increased with the severity of the RLS and had some influence on the patient's cognitive function. Sleep disorders were closely related to RLSRS and HAMD.

Comparison of human IgG glycopeptides separation using mixed-mode hydrophilic interaction/ion-exchange liquid chromatography and reversed-phase mode

Glycoproteomics is a challenging branch of proteomics because of the micro- and macro-heterogeneity of protein glycosylation. Hydrophilic interaction liquid chromatography (HILIC) is an advantageous alternative to reversed-phase chromatography for intact glycopeptide separation prior to their identification by mass spectrometry. Nowadays, several HILIC columns differing in used chemistries are commercially available. However, there is a lack of comparative studies assessing their performance, and thus providing guidance for the selection of an adequate stationary phase for different glycoproteomics applications. Here, we compare three HILIC columns recently developed by Advanced Chromatography Technologies (ACE)- with unfunctionalized (HILIC-A), polyhydroxy functionalized (HILIC-N), and aminopropyl functionalized (HILIC-B) silica- with a C18 reversed-phase column in the separation of human immunoglobulin G glycopeptides. HILIC-A and HILIC-B exhibit mixed-mode separation combining hydrophilic and ion-exchange interactions for analyte retention. Expectably, reversed-phase mode successfully separated clusters of immunoglobulin G1 and immunoglobulin G2 glycopeptides, which differ in amino acid sequence, but was not able to adequately separate different glycoforms of the same peptide. All ACE HILIC columns showed higher separation power for different glycoforms, and we show that each column separates a different group of glycopeptides more effectively than the others. Moreover, HILIC-A and HILIC-N columns separated the isobaric A2G1F1 glycopeptides of immunoglobulin G, and thus showed the potential for the elucidation of the structure of isomeric glycoforms. Furthermore, the possible retention mechanism for the HILIC columns is discussed on the basis of the determined chromatographic parameters.

Comparative Analysis of Different N-glycan Preparation Approaches and Development of Optimized Solid-Phase Permethylation Using Mass Spectrometry

Protein N-glycosylation characterization is challenging due to structural micro- and macro-heterogeneity. Although various N-glycan preparation strategies, including purification and derivatization, have been previously developed prior to mass spectrometric analysis, systematic evaluation still needs to be performed. This study compared the different N-glycan purification strategies, including filter-aided sample preparation, de-N-glycosylated protein precipitation, and trypsin digestion followed by reversed phase-based solid-phase extraction, and derivatization approaches, such as solid-phase permethylation, reductive amination, and reduction. With the comparative analysis, an optimized solid-phase permethylation (OSPP) workflow was developed for mass spectrometric N-glycomics, showing simplified analysis for N-glycan compositions and high yields using etanercept. The N-glycan samples released from trastuzumab and adalimumab were utilized to test OSPP to obtain their N-glycan profiles using mass spectrometry. Based on different standard procedures across laboratories, this study provides the reference for analysts to select an appropriate N-glycan preparation method with their research purposes.

N-Glycomics of Cerebrospinal Fluid: Method Comparison

Cerebrospinal fluid (CSF) contains valuable biological and neurological information. However, its glycomics analysis is hampered due to the low amount of protein in the biofluid, as has been demonstrated by other glycomics studies using a substantial amount of CSF. In this work, we investigated different N-glycan sample preparation approaches to develop a more sensitive method. These methods, one with an increased amount of buffer solution during the N-glycan release step with a lower amount of sample volume and the other with Filter-Aided N-Glycan Separation (FANGS), were compared with recent work to demonstrate their effectiveness. It was demonstrated that an increased amount of buffer solution showed higher intensity in comparison to the previously published method and FANGS. This suggested that digestion efficiency during the N-glycan release step was not in an optimal condition from the previously published method, and that there is a substantial loss of sample with FANGS when preparing N-glycans from CSF.